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» Approximate Learning of Dynamic Models
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ESANN
2006
15 years 6 months ago
Extended model of conditioned learning within latent inhibition
Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
Nicolas Gomond, Jean Marc Salotti
IROS
2006
IEEE
135views Robotics» more  IROS 2006»
15 years 10 months ago
Bio-inspired Model of Robot Adaptive Learning and Mapping
- In this paper we present a model designed on the basis of the neurophysiology of the rat hippocampus to control the navigation of a real robot. The model allows the robot to lear...
Alejandra Barrera Ramirez, Alfredo Weitzenfeld Rid...
NIPS
2007
15 years 6 months ago
Online Linear Regression and Its Application to Model-Based Reinforcement Learning
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
Alexander L. Strehl, Michael L. Littman
159
Voted
CORR
2010
Springer
182views Education» more  CORR 2010»
15 years 4 months ago
Fast Convergence of Natural Bargaining Dynamics in Exchange Networks
Bargaining networks model the behavior of a set of players who need to reach pairwise agreements for making profits. Nash bargaining solutions in this context correspond to soluti...
Yashodhan Kanoria, Mohsen Bayati, Christian Borgs,...
GLVLSI
2005
IEEE
103views VLSI» more  GLVLSI 2005»
15 years 10 months ago
Causal probabilistic input dependency learning for switching model in VLSI circuits
Switching model captures the data-driven uncertainty in logic circuits in a comprehensive probabilistic framework. Switching is a critical factor that influences dynamic, active ...
Nirmal Ramalingam, Sanjukta Bhanja